eAnalytics: a model of a learning analytics visualization system

Abstract

Collecting big data from e-learning is already a fact. Huge opportunities open up for learning analytics to deeply understand and effectively optimize the process of teaching and learning. At the same time, large amounts of data require more time, efforts and resources to extract useful information from them. This paper presents a research proposing a model of a learning analytics system aiming through advances in big data visualization methods to facilitate data interpretation and assist timely and accurate decision making. The study describes an architectural model called eAnalytics. It consists of three main components: Data sources connection, Data management and Learning analytics visualization. The last component provides a choice of three methods for visualizing analytics: via a ready-to-use virtual dashboard, via a virtual dashboard template, or by composing personalized analytics. The paper depicts the prototyping of the model and its validation by conducting two types of testing: for functional compliance and by applying "Think aloud" protocol. Finally, important conclusions are drawn and some directions for future work are outlined.